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Demars BOL, Dörsch P. Estimation of ecosystem respiration and photosynthesis in supersaturated stream water downstream of a hydropower plant. WATER RESEARCH 2023; 247:120842. [PMID: 37950952 DOI: 10.1016/j.watres.2023.120842] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 11/01/2023] [Accepted: 11/05/2023] [Indexed: 11/13/2023]
Abstract
The estimation of whole stream metabolism, as determined by photosynthesis and respiration, is critical to our understanding of carbon cycling and carbon subsidies to aquatic food-webs. The mass development of aquatic plants is a worldwide problem for human activities and often occurs in regulated rivers, altering biodiversity and ecosystem functions. Hydropower plants supersaturate water with gases and prevent the use of common whole stream metabolism models to estimate ecosystem respiration. Here we used the inert noble gas argon to parse out biological from physical processes in stream metabolism calculations. We coupled the O2:Ar ratio determined by gas chromatography in grab samples with in-situ oxygen concentrations measured by an optode to estimate aquatic plant photosynthesis and ecosystem respiration during supersaturation events through a parsimonious approach. The results compared well with a more complicated two-station model based on O2 mass balances in non-supersatured water, and with associated changes in dissolved CO2 (or dissolved inorganic carbon). This new method provides an independent approach to evaluate alternative corrections of dissolved oxygen data (e.g. through the use of total dissolved gases) in long term studies. The use of photosynthesis-irradiance models allows the determination of light parameters such as the onset of light saturation or low light use efficiency, which could be used for inverse modelling. The use of the O2:Ar approach to correct for oversaturation may become more applicable with the emergence of portable mass inlet mass spectrometers (MIMS). Photosynthesis was modest (2.9-5.8 g O2 m2 day-1) compared to other rivers with submerged vegetation, likely indicating nutrient co-limitations (CO2, inorganic N and P). Respiration was very low (-2.1 to -3.9 g O2 m2 day-1) likely due to a lack of allochthonous carbon supply and sandy sediment.
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Affiliation(s)
- Benoît O L Demars
- Norwegian Institute for Water Research (NIVA), Økernveien 94, Oslo 0579, Norway.
| | - Peter Dörsch
- Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Ås 1432, Norway
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Blaszczak JR, Yackulic CB, Shriver RK, Hall RO. Models of underlying autotrophic biomass dynamics fit to daily river ecosystem productivity estimates improve understanding of ecosystem disturbance and resilience. Ecol Lett 2023; 26:1510-1522. [PMID: 37353910 DOI: 10.1111/ele.14269] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 05/20/2023] [Accepted: 05/23/2023] [Indexed: 06/25/2023]
Abstract
Directly observing autotrophic biomass at ecologically relevant frequencies is difficult in many ecosystems, hampering our ability to predict productivity through time. Since disturbances can impart distinct reductions in river productivity through time by modifying underlying standing stocks of biomass, mechanistic models fit to productivity time series can infer underlying biomass dynamics. We incorporated biomass dynamics into a river ecosystem productivity model for six rivers to identify disturbance flow thresholds and understand the resilience of primary producers. The magnitude of flood necessary to disturb biomass and thereby reduce ecosystem productivity was consistently lower than the more commonly used disturbance flow threshold of the flood magnitude necessary to mobilize river bed sediment. The estimated daily maximum percent increase in biomass (a proxy for resilience) ranged from 5% to 42% across rivers. Our latent biomass model improves understanding of disturbance thresholds and recovery patterns of autotrophic biomass within river ecosystems.
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Affiliation(s)
- Joanna R Blaszczak
- Department of Natural Resources and Environmental Science, University of Nevada, Reno, Nevada, USA
- Flathead Lake Biological Station, University of Montana, Polson, Montana, USA
| | - Charles B Yackulic
- U.S. Geological Survey, Southwest Biological Science Center, Flagstaff, Arizona, USA
| | - Robert K Shriver
- Department of Natural Resources and Environmental Science, University of Nevada, Reno, Nevada, USA
| | - Robert O Hall
- Flathead Lake Biological Station, University of Montana, Polson, Montana, USA
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3
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River ecosystem metabolism and carbon biogeochemistry in a changing world. Nature 2023; 613:449-459. [PMID: 36653564 DOI: 10.1038/s41586-022-05500-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 10/31/2022] [Indexed: 01/20/2023]
Abstract
River networks represent the largest biogeochemical nexus between the continents, ocean and atmosphere. Our current understanding of the role of rivers in the global carbon cycle remains limited, which makes it difficult to predict how global change may alter the timing and spatial distribution of riverine carbon sequestration and greenhouse gas emissions. Here we review the state of river ecosystem metabolism research and synthesize the current best available estimates of river ecosystem metabolism. We quantify the organic and inorganic carbon flux from land to global rivers and show that their net ecosystem production and carbon dioxide emissions shift the organic to inorganic carbon balance en route from land to the coastal ocean. Furthermore, we discuss how global change may affect river ecosystem metabolism and related carbon fluxes and identify research directions that can help to develop better predictions of the effects of global change on riverine ecosystem processes. We argue that a global river observing system will play a key role in understanding river networks and their future evolution in the context of the global carbon budget.
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Deemer BR, Yackulic CB, Hall RO, Dodrill MJ, Kennedy TA, Muehlbauer JD, Topping DJ, Voichick N, Yard MD. Experimental reductions in subdaily flow fluctuations increased gross primary productivity for 425 river kilometers downstream. PNAS NEXUS 2022; 1:pgac094. [PMID: 36741441 PMCID: PMC9896909 DOI: 10.1093/pnasnexus/pgac094] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 06/17/2022] [Indexed: 02/07/2023]
Abstract
Aquatic primary production is the foundation of many river food webs. Dams change the physical template of rivers, often driving food webs toward greater reliance on aquatic primary production. Nonetheless, the effects of regulated flow regimes on primary production are poorly understood. Load following is a common dam flow management strategy that involves subdaily changes in water releases proportional to fluctuations in electrical power demand. This flow regime causes an artificial tide, wetting and drying channel margins and altering river depth and water clarity, all processes that are likely to affect primary production. In collaboration with dam operators, we designed an experimental flow regime whose goal was to mitigate negative effects of load following on ecosystem processes. The experimental flow contrasted steady-low flows on weekends with load following flows on weekdays. Here, we quantify the effect of this experimental flow on springtime gross primary production (GPP) 90-to-425 km downstream of Glen Canyon Dam on the Colorado River, AZ, USA. GPP during steady-low flows was 41% higher than during load following flows, mostly owing to nonlinear reductions in sediment-driven turbidity. The experimental flow increased weekly GPP even after controlling for variation in weekly mean discharge, demonstrating a negative effect of load following on GPP. We estimate that this environmental flow increased springtime carbon fixation by 0.27 g C m-2 d-1, which is ecologically meaningful considering median C fixation in 356 US rivers of 0.44 g C m-2 d-1 and the fact that native fish populations in this river are food-limited.
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Affiliation(s)
| | - Charles B Yackulic
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA
| | - Robert O Hall
- Flathead Lake Biological Station, University of Montana, Polson, MT 59860, USA
| | - Michael J Dodrill
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA,Columbia River Research Lab, U.S. Geological Survey, Cook, WA 98605, USA
| | - Theodore A Kennedy
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA
| | - Jeffrey D Muehlbauer
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA,Alaska Cooperative Fish and Wildlife Research Unit, U.S. Geological Survey, Fairbanks, AK 99775 , USA
| | - David J Topping
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA
| | - Nicholas Voichick
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA
| | - Michael D Yard
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA
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Abstract
Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management.
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